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<li class="navelem"><a class="el" href="../../d2/d75/namespacecv.html">cv</a></li><li class="navelem"><a class="el" href="../../d8/df1/namespacecv_1_1ml.html">ml</a></li><li class="navelem"><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html">DTrees</a></li>  </ul>
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<a href="#nested-classes">Classes</a> |
<a href="#pub-types">Public Types</a> |
<a href="#pub-methods">Public Member Functions</a> |
<a href="#pub-static-methods">Static Public Member Functions</a> |
<a href="../../de/d66/classcv_1_1ml_1_1DTrees-members.html">List of all members</a>  </div>
  <div class="headertitle">
<div class="title">cv::ml::DTrees Class Reference<span class="mlabels"><span class="mlabel">abstract</span></span><div class="ingroups"><a class="el" href="../../dd/ded/group__ml.html">Machine Learning</a></div></div>  </div>
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<p>The class represents a single decision tree or a collection of decision trees.  
 <a href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#details">More...</a></p>
<p><code>#include &lt;opencv2/ml.hpp&gt;</code></p>
<div class="dynheader">
Inheritance diagram for cv::ml::DTrees:</div>
<div class="dyncontent">
 <div class="center">
  <img alt="" src="../../d8/d89/classcv_1_1ml_1_1DTrees.png" usemap="#cv::ml::DTrees_map"/>
  <map id="cv::ml::DTrees_map" name="cv::ml::DTrees_map">
<area alt="cv::ml::StatModel" coords="58,56,164,80" href="../../db/d7d/classcv_1_1ml_1_1StatModel.html" shape="rect" title="Base class for statistical models in OpenCV ML. "/>
<area alt="cv::Algorithm" coords="58,0,164,24" href="../../d3/d46/classcv_1_1Algorithm.html" shape="rect" title="This is a base class for all more or less complex algorithms in OpenCV. "/>
<area alt="cv::ml::Boost" coords="0,168,106,192" href="../../d6/d7a/classcv_1_1ml_1_1Boost.html" shape="rect" title="Boosted tree classifier derived from DTrees. "/>
<area alt="cv::ml::RTrees" coords="116,168,222,192" href="../../d0/d65/classcv_1_1ml_1_1RTrees.html" shape="rect" title="The class implements the random forest predictor. "/>
</map>
 </div></div>
<table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="nested-classes"></a>
Classes</h2></td></tr>
<tr class="memitem:"><td align="right" class="memItemLeft" valign="top">class  </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d4/d7d/classcv_1_1ml_1_1DTrees_1_1Node.html">Node</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft"> </td><td class="mdescRight">The class represents a decision tree node.  <a href="../../d4/d7d/classcv_1_1ml_1_1DTrees_1_1Node.html#details">More...</a><br/></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:"><td align="right" class="memItemLeft" valign="top">class  </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d9/d37/classcv_1_1ml_1_1DTrees_1_1Split.html">Split</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft"> </td><td class="mdescRight">The class represents split in a decision tree.  <a href="../../d9/d37/classcv_1_1ml_1_1DTrees_1_1Split.html#details">More...</a><br/></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2"> </td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-types"></a>
Public Types</h2></td></tr>
<tr class="memitem:a7afa5cd2289fb88989c0ab1b8b5d8ac2"><td align="right" class="memItemLeft" valign="top">enum  </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#a7afa5cd2289fb88989c0ab1b8b5d8ac2">Flags</a> { <br/>
  <a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#a7afa5cd2289fb88989c0ab1b8b5d8ac2af0192db97208b67118f642530da47332">PREDICT_AUTO</a> =0, 
<br/>
  <a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#a7afa5cd2289fb88989c0ab1b8b5d8ac2a1d3f6687120ea6b337f6a91234529a13">PREDICT_SUM</a> =(1&lt;&lt;8), 
<br/>
  <a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#a7afa5cd2289fb88989c0ab1b8b5d8ac2ad753bae4672b471203e418d820c00e85">PREDICT_MAX_VOTE</a> =(2&lt;&lt;8), 
<br/>
  <a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#a7afa5cd2289fb88989c0ab1b8b5d8ac2a59a0cd54206e4092bc2bff1ce50c8afa">PREDICT_MASK</a> =(3&lt;&lt;8)
<br/>
 }</td></tr>
<tr class="separator:a7afa5cd2289fb88989c0ab1b8b5d8ac2"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="inherit_header pub_types_classcv_1_1ml_1_1StatModel"><td colspan="2" onclick="javascript:toggleInherit('pub_types_classcv_1_1ml_1_1StatModel')"><img alt="-" src="../../closed.png"/> Public Types inherited from <a class="el" href="../../db/d7d/classcv_1_1ml_1_1StatModel.html">cv::ml::StatModel</a></td></tr>
<tr class="memitem:af1ea864e1c19796e6264ebb3950c0b9a inherit pub_types_classcv_1_1ml_1_1StatModel"><td align="right" class="memItemLeft" valign="top">enum  </td><td class="memItemRight" valign="bottom"><a class="el" href="../../db/d7d/classcv_1_1ml_1_1StatModel.html#af1ea864e1c19796e6264ebb3950c0b9a">Flags</a> { <br/>
  <a class="el" href="../../db/d7d/classcv_1_1ml_1_1StatModel.html#af1ea864e1c19796e6264ebb3950c0b9aa397fde9eaadd4efb07af6a7fbacea6cd">UPDATE_MODEL</a> = 1, 
<br/>
  <a class="el" href="../../db/d7d/classcv_1_1ml_1_1StatModel.html#af1ea864e1c19796e6264ebb3950c0b9aa639a8ea2b61c2bf03f87cf4c4a5bd824">RAW_OUTPUT</a> =1, 
<br/>
  <a class="el" href="../../db/d7d/classcv_1_1ml_1_1StatModel.html#af1ea864e1c19796e6264ebb3950c0b9aae860ef9fda481bb6730e8794009c99b5">COMPRESSED_INPUT</a> =2, 
<br/>
  <a class="el" href="../../db/d7d/classcv_1_1ml_1_1StatModel.html#af1ea864e1c19796e6264ebb3950c0b9aa0cdfa2b3b9c5947d9a80bcca7eac485f">PREPROCESSED_INPUT</a> =4
<br/>
 }</td></tr>
<tr class="separator:af1ea864e1c19796e6264ebb3950c0b9a inherit pub_types_classcv_1_1ml_1_1StatModel"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-methods"></a>
Public Member Functions</h2></td></tr>
<tr class="memitem:abfced3f2d3bf13b39c94e4a3fecc4309"><td align="right" class="memItemLeft" valign="top">virtual int </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#abfced3f2d3bf13b39c94e4a3fecc4309">getCVFolds</a> () const =0</td></tr>
<tr class="separator:abfced3f2d3bf13b39c94e4a3fecc4309"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:ad7dea805ae861c26fdd0b79eb34b3c24"><td align="right" class="memItemLeft" valign="top">virtual int </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#ad7dea805ae861c26fdd0b79eb34b3c24">getMaxCategories</a> () const =0</td></tr>
<tr class="separator:ad7dea805ae861c26fdd0b79eb34b3c24"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:ac41b80cb9e2ea0d477425052f9692104"><td align="right" class="memItemLeft" valign="top">virtual int </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#ac41b80cb9e2ea0d477425052f9692104">getMaxDepth</a> () const =0</td></tr>
<tr class="separator:ac41b80cb9e2ea0d477425052f9692104"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a277c2ccecfa7fc65d1d474b56450e126"><td align="right" class="memItemLeft" valign="top">virtual int </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#a277c2ccecfa7fc65d1d474b56450e126">getMinSampleCount</a> () const =0</td></tr>
<tr class="separator:a277c2ccecfa7fc65d1d474b56450e126"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:ae4ffa17349a0094c5cded6e92042ffc2"><td align="right" class="memItemLeft" valign="top">virtual const std::vector&lt; <a class="el" href="../../d4/d7d/classcv_1_1ml_1_1DTrees_1_1Node.html">Node</a> &gt; &amp; </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#ae4ffa17349a0094c5cded6e92042ffc2">getNodes</a> () const =0</td></tr>
<tr class="memdesc:ae4ffa17349a0094c5cded6e92042ffc2"><td class="mdescLeft"> </td><td class="mdescRight">Returns all the nodes.  <a href="#ae4ffa17349a0094c5cded6e92042ffc2">More...</a><br/></td></tr>
<tr class="separator:ae4ffa17349a0094c5cded6e92042ffc2"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a152badc1f5a4963ef9d43d7e7395bd3b"><td align="right" class="memItemLeft" valign="top">virtual <a class="el" href="../../d3/d63/classcv_1_1Mat.html">cv::Mat</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#a152badc1f5a4963ef9d43d7e7395bd3b">getPriors</a> () const =0</td></tr>
<tr class="memdesc:a152badc1f5a4963ef9d43d7e7395bd3b"><td class="mdescLeft"> </td><td class="mdescRight">The array of a priori class probabilities, sorted by the class label value.  <a href="#a152badc1f5a4963ef9d43d7e7395bd3b">More...</a><br/></td></tr>
<tr class="separator:a152badc1f5a4963ef9d43d7e7395bd3b"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:ab7ec8342deddac53ebbb92145c992db7"><td align="right" class="memItemLeft" valign="top">virtual float </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#ab7ec8342deddac53ebbb92145c992db7">getRegressionAccuracy</a> () const =0</td></tr>
<tr class="separator:ab7ec8342deddac53ebbb92145c992db7"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:af99b15e5769c614bb1f1e16330b6fa4f"><td align="right" class="memItemLeft" valign="top">virtual const std::vector&lt; int &gt; &amp; </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#af99b15e5769c614bb1f1e16330b6fa4f">getRoots</a> () const =0</td></tr>
<tr class="memdesc:af99b15e5769c614bb1f1e16330b6fa4f"><td class="mdescLeft"> </td><td class="mdescRight">Returns indices of root nodes.  <a href="#af99b15e5769c614bb1f1e16330b6fa4f">More...</a><br/></td></tr>
<tr class="separator:af99b15e5769c614bb1f1e16330b6fa4f"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a23bd587736aa6c658966025cfff3f4a3"><td align="right" class="memItemLeft" valign="top">virtual const std::vector&lt; <a class="el" href="../../d9/d37/classcv_1_1ml_1_1DTrees_1_1Split.html">Split</a> &gt; &amp; </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#a23bd587736aa6c658966025cfff3f4a3">getSplits</a> () const =0</td></tr>
<tr class="memdesc:a23bd587736aa6c658966025cfff3f4a3"><td class="mdescLeft"> </td><td class="mdescRight">Returns all the splits.  <a href="#a23bd587736aa6c658966025cfff3f4a3">More...</a><br/></td></tr>
<tr class="separator:a23bd587736aa6c658966025cfff3f4a3"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:ab4edebdd513c1937dfa8f444931f6a7a"><td align="right" class="memItemLeft" valign="top">virtual const std::vector&lt; int &gt; &amp; </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#ab4edebdd513c1937dfa8f444931f6a7a">getSubsets</a> () const =0</td></tr>
<tr class="memdesc:ab4edebdd513c1937dfa8f444931f6a7a"><td class="mdescLeft"> </td><td class="mdescRight">Returns all the bitsets for categorical splits.  <a href="#ab4edebdd513c1937dfa8f444931f6a7a">More...</a><br/></td></tr>
<tr class="separator:ab4edebdd513c1937dfa8f444931f6a7a"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a905b23962a6c393a87b79bcc086cc6c2"><td align="right" class="memItemLeft" valign="top">virtual bool </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#a905b23962a6c393a87b79bcc086cc6c2">getTruncatePrunedTree</a> () const =0</td></tr>
<tr class="separator:a905b23962a6c393a87b79bcc086cc6c2"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a5d8bd6934507c56905f93b5b8c7d1584"><td align="right" class="memItemLeft" valign="top">virtual bool </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#a5d8bd6934507c56905f93b5b8c7d1584">getUse1SERule</a> () const =0</td></tr>
<tr class="separator:a5d8bd6934507c56905f93b5b8c7d1584"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a566708bb8841067f146afae81b6219f4"><td align="right" class="memItemLeft" valign="top">virtual bool </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#a566708bb8841067f146afae81b6219f4">getUseSurrogates</a> () const =0</td></tr>
<tr class="separator:a566708bb8841067f146afae81b6219f4"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a082ed33b1dd2101152dd33bdc2847404"><td align="right" class="memItemLeft" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#a082ed33b1dd2101152dd33bdc2847404">setCVFolds</a> (int val)=0</td></tr>
<tr class="separator:a082ed33b1dd2101152dd33bdc2847404"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a6d1571c10e5d72f8df7f102b916d704f"><td align="right" class="memItemLeft" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#a6d1571c10e5d72f8df7f102b916d704f">setMaxCategories</a> (int val)=0</td></tr>
<tr class="separator:a6d1571c10e5d72f8df7f102b916d704f"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:ab2192b5631da2d30eaaebdb12015f477"><td align="right" class="memItemLeft" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#ab2192b5631da2d30eaaebdb12015f477">setMaxDepth</a> (int val)=0</td></tr>
<tr class="separator:ab2192b5631da2d30eaaebdb12015f477"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:abe34fc6e9a172b9e334abcca94e28fb6"><td align="right" class="memItemLeft" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#abe34fc6e9a172b9e334abcca94e28fb6">setMinSampleCount</a> (int val)=0</td></tr>
<tr class="separator:abe34fc6e9a172b9e334abcca94e28fb6"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a66756433f31db77a5511fc3f85403bd9"><td align="right" class="memItemLeft" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#a66756433f31db77a5511fc3f85403bd9">setPriors</a> (const <a class="el" href="../../d3/d63/classcv_1_1Mat.html">cv::Mat</a> &amp;val)=0</td></tr>
<tr class="memdesc:a66756433f31db77a5511fc3f85403bd9"><td class="mdescLeft"> </td><td class="mdescRight">The array of a priori class probabilities, sorted by the class label value.  <a href="#a66756433f31db77a5511fc3f85403bd9">More...</a><br/></td></tr>
<tr class="separator:a66756433f31db77a5511fc3f85403bd9"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a936a3b56ccc5684f279dfd76bbea0247"><td align="right" class="memItemLeft" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#a936a3b56ccc5684f279dfd76bbea0247">setRegressionAccuracy</a> (float val)=0</td></tr>
<tr class="separator:a936a3b56ccc5684f279dfd76bbea0247"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a6f2663a08abc3e872bd3f3a53a84615c"><td align="right" class="memItemLeft" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#a6f2663a08abc3e872bd3f3a53a84615c">setTruncatePrunedTree</a> (bool val)=0</td></tr>
<tr class="separator:a6f2663a08abc3e872bd3f3a53a84615c"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a08089831f9a07e0ce6a5e5faccdf31f6"><td align="right" class="memItemLeft" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#a08089831f9a07e0ce6a5e5faccdf31f6">setUse1SERule</a> (bool val)=0</td></tr>
<tr class="separator:a08089831f9a07e0ce6a5e5faccdf31f6"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a33d8fec217d423609a9f29a0a787111c"><td align="right" class="memItemLeft" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#a33d8fec217d423609a9f29a0a787111c">setUseSurrogates</a> (bool val)=0</td></tr>
<tr class="separator:a33d8fec217d423609a9f29a0a787111c"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="inherit_header pub_methods_classcv_1_1ml_1_1StatModel"><td colspan="2" onclick="javascript:toggleInherit('pub_methods_classcv_1_1ml_1_1StatModel')"><img alt="-" src="../../closed.png"/> Public Member Functions inherited from <a class="el" href="../../db/d7d/classcv_1_1ml_1_1StatModel.html">cv::ml::StatModel</a></td></tr>
<tr class="memitem:aa6a71b1ee5b7fa0b07b55e77106cda13 inherit pub_methods_classcv_1_1ml_1_1StatModel"><td align="right" class="memItemLeft" valign="top">virtual float </td><td class="memItemRight" valign="bottom"><a class="el" href="../../db/d7d/classcv_1_1ml_1_1StatModel.html#aa6a71b1ee5b7fa0b07b55e77106cda13">calcError</a> (const <a class="el" href="../../dc/d84/group__core__basic.html#ga6395ca871a678020c4a31fadf7e8cc63">Ptr</a>&lt; <a class="el" href="../../dc/d32/classcv_1_1ml_1_1TrainData.html">TrainData</a> &gt; &amp;data, bool test, <a class="el" href="../../dc/d84/group__core__basic.html#gaad17fda1d0f0d1ee069aebb1df2913c0">OutputArray</a> resp) const</td></tr>
<tr class="memdesc:aa6a71b1ee5b7fa0b07b55e77106cda13 inherit pub_methods_classcv_1_1ml_1_1StatModel"><td class="mdescLeft"> </td><td class="mdescRight">Computes error on the training or test dataset.  <a href="../../db/d7d/classcv_1_1ml_1_1StatModel.html#aa6a71b1ee5b7fa0b07b55e77106cda13">More...</a><br/></td></tr>
<tr class="separator:aa6a71b1ee5b7fa0b07b55e77106cda13 inherit pub_methods_classcv_1_1ml_1_1StatModel"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a80afceed1710367d32d6232374162b97 inherit pub_methods_classcv_1_1ml_1_1StatModel"><td align="right" class="memItemLeft" valign="top">virtual bool </td><td class="memItemRight" valign="bottom"><a class="el" href="../../db/d7d/classcv_1_1ml_1_1StatModel.html#a80afceed1710367d32d6232374162b97">empty</a> () const <a class="el" href="../../db/de0/group__core__utils.html#ga4d89d63e402ef9ddc48e18e21180fe4a">CV_OVERRIDE</a></td></tr>
<tr class="memdesc:a80afceed1710367d32d6232374162b97 inherit pub_methods_classcv_1_1ml_1_1StatModel"><td class="mdescLeft"> </td><td class="mdescRight">Returns true if the <a class="el" href="../../d3/d46/classcv_1_1Algorithm.html" title="This is a base class for all more or less complex algorithms in OpenCV. ">Algorithm</a> is empty (e.g. in the very beginning or after unsuccessful read.  <a href="../../db/d7d/classcv_1_1ml_1_1StatModel.html#a80afceed1710367d32d6232374162b97">More...</a><br/></td></tr>
<tr class="separator:a80afceed1710367d32d6232374162b97 inherit pub_methods_classcv_1_1ml_1_1StatModel"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a783b92c436c7a2978e2d4bbb3cfb6e0c inherit pub_methods_classcv_1_1ml_1_1StatModel"><td align="right" class="memItemLeft" valign="top">virtual int </td><td class="memItemRight" valign="bottom"><a class="el" href="../../db/d7d/classcv_1_1ml_1_1StatModel.html#a783b92c436c7a2978e2d4bbb3cfb6e0c">getVarCount</a> () const =0</td></tr>
<tr class="memdesc:a783b92c436c7a2978e2d4bbb3cfb6e0c inherit pub_methods_classcv_1_1ml_1_1StatModel"><td class="mdescLeft"> </td><td class="mdescRight">Returns the number of variables in training samples.  <a href="../../db/d7d/classcv_1_1ml_1_1StatModel.html#a783b92c436c7a2978e2d4bbb3cfb6e0c">More...</a><br/></td></tr>
<tr class="separator:a783b92c436c7a2978e2d4bbb3cfb6e0c inherit pub_methods_classcv_1_1ml_1_1StatModel"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a1121a835feedefdcdb8624966567aec6 inherit pub_methods_classcv_1_1ml_1_1StatModel"><td align="right" class="memItemLeft" valign="top">virtual bool </td><td class="memItemRight" valign="bottom"><a class="el" href="../../db/d7d/classcv_1_1ml_1_1StatModel.html#a1121a835feedefdcdb8624966567aec6">isClassifier</a> () const =0</td></tr>
<tr class="memdesc:a1121a835feedefdcdb8624966567aec6 inherit pub_methods_classcv_1_1ml_1_1StatModel"><td class="mdescLeft"> </td><td class="mdescRight">Returns true if the model is classifier.  <a href="../../db/d7d/classcv_1_1ml_1_1StatModel.html#a1121a835feedefdcdb8624966567aec6">More...</a><br/></td></tr>
<tr class="separator:a1121a835feedefdcdb8624966567aec6 inherit pub_methods_classcv_1_1ml_1_1StatModel"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:aab380b59eb30b50254ef1b804774c4d8 inherit pub_methods_classcv_1_1ml_1_1StatModel"><td align="right" class="memItemLeft" valign="top">virtual bool </td><td class="memItemRight" valign="bottom"><a class="el" href="../../db/d7d/classcv_1_1ml_1_1StatModel.html#aab380b59eb30b50254ef1b804774c4d8">isTrained</a> () const =0</td></tr>
<tr class="memdesc:aab380b59eb30b50254ef1b804774c4d8 inherit pub_methods_classcv_1_1ml_1_1StatModel"><td class="mdescLeft"> </td><td class="mdescRight">Returns true if the model is trained.  <a href="../../db/d7d/classcv_1_1ml_1_1StatModel.html#aab380b59eb30b50254ef1b804774c4d8">More...</a><br/></td></tr>
<tr class="separator:aab380b59eb30b50254ef1b804774c4d8 inherit pub_methods_classcv_1_1ml_1_1StatModel"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a1a7e49e1febd10392452727498771bc1 inherit pub_methods_classcv_1_1ml_1_1StatModel"><td align="right" class="memItemLeft" valign="top">virtual float </td><td class="memItemRight" valign="bottom"><a class="el" href="../../db/d7d/classcv_1_1ml_1_1StatModel.html#a1a7e49e1febd10392452727498771bc1">predict</a> (<a class="el" href="../../dc/d84/group__core__basic.html#ga353a9de602fe76c709e12074a6f362ba">InputArray</a> samples, <a class="el" href="../../dc/d84/group__core__basic.html#gaad17fda1d0f0d1ee069aebb1df2913c0">OutputArray</a> results=<a class="el" href="../../dc/d84/group__core__basic.html#gad9287b23bba2fed753b36ef561ae7346">noArray</a>(), int flags=0) const =0</td></tr>
<tr class="memdesc:a1a7e49e1febd10392452727498771bc1 inherit pub_methods_classcv_1_1ml_1_1StatModel"><td class="mdescLeft"> </td><td class="mdescRight">Predicts response(s) for the provided sample(s)  <a href="../../db/d7d/classcv_1_1ml_1_1StatModel.html#a1a7e49e1febd10392452727498771bc1">More...</a><br/></td></tr>
<tr class="separator:a1a7e49e1febd10392452727498771bc1 inherit pub_methods_classcv_1_1ml_1_1StatModel"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:af96a0e04f1677a835cc25263c7db3c0c inherit pub_methods_classcv_1_1ml_1_1StatModel"><td align="right" class="memItemLeft" valign="top">virtual bool </td><td class="memItemRight" valign="bottom"><a class="el" href="../../db/d7d/classcv_1_1ml_1_1StatModel.html#af96a0e04f1677a835cc25263c7db3c0c">train</a> (const <a class="el" href="../../dc/d84/group__core__basic.html#ga6395ca871a678020c4a31fadf7e8cc63">Ptr</a>&lt; <a class="el" href="../../dc/d32/classcv_1_1ml_1_1TrainData.html">TrainData</a> &gt; &amp;trainData, int flags=0)</td></tr>
<tr class="memdesc:af96a0e04f1677a835cc25263c7db3c0c inherit pub_methods_classcv_1_1ml_1_1StatModel"><td class="mdescLeft"> </td><td class="mdescRight">Trains the statistical model.  <a href="../../db/d7d/classcv_1_1ml_1_1StatModel.html#af96a0e04f1677a835cc25263c7db3c0c">More...</a><br/></td></tr>
<tr class="separator:af96a0e04f1677a835cc25263c7db3c0c inherit pub_methods_classcv_1_1ml_1_1StatModel"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:aeb25a75f438864fb25af182fb4b1b96f inherit pub_methods_classcv_1_1ml_1_1StatModel"><td align="right" class="memItemLeft" valign="top">virtual bool </td><td class="memItemRight" valign="bottom"><a class="el" href="../../db/d7d/classcv_1_1ml_1_1StatModel.html#aeb25a75f438864fb25af182fb4b1b96f">train</a> (<a class="el" href="../../dc/d84/group__core__basic.html#ga353a9de602fe76c709e12074a6f362ba">InputArray</a> samples, int layout, <a class="el" href="../../dc/d84/group__core__basic.html#ga353a9de602fe76c709e12074a6f362ba">InputArray</a> responses)</td></tr>
<tr class="memdesc:aeb25a75f438864fb25af182fb4b1b96f inherit pub_methods_classcv_1_1ml_1_1StatModel"><td class="mdescLeft"> </td><td class="mdescRight">Trains the statistical model.  <a href="../../db/d7d/classcv_1_1ml_1_1StatModel.html#aeb25a75f438864fb25af182fb4b1b96f">More...</a><br/></td></tr>
<tr class="separator:aeb25a75f438864fb25af182fb4b1b96f inherit pub_methods_classcv_1_1ml_1_1StatModel"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="inherit_header pub_methods_classcv_1_1Algorithm"><td colspan="2" onclick="javascript:toggleInherit('pub_methods_classcv_1_1Algorithm')"><img alt="-" src="../../closed.png"/> Public Member Functions inherited from <a class="el" href="../../d3/d46/classcv_1_1Algorithm.html">cv::Algorithm</a></td></tr>
<tr class="memitem:a827c8b2781ed17574805f373e6054ff1 inherit pub_methods_classcv_1_1Algorithm"><td align="right" class="memItemLeft" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d3/d46/classcv_1_1Algorithm.html#a827c8b2781ed17574805f373e6054ff1">Algorithm</a> ()</td></tr>
<tr class="separator:a827c8b2781ed17574805f373e6054ff1 inherit pub_methods_classcv_1_1Algorithm"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a8ae826127fa0f1f8d10a24841bd376f8 inherit pub_methods_classcv_1_1Algorithm"><td align="right" class="memItemLeft" valign="top">virtual </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d3/d46/classcv_1_1Algorithm.html#a8ae826127fa0f1f8d10a24841bd376f8">~Algorithm</a> ()</td></tr>
<tr class="separator:a8ae826127fa0f1f8d10a24841bd376f8 inherit pub_methods_classcv_1_1Algorithm"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:aec9c965448e4dc851d7cacd3abd84cd1 inherit pub_methods_classcv_1_1Algorithm"><td align="right" class="memItemLeft" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d3/d46/classcv_1_1Algorithm.html#aec9c965448e4dc851d7cacd3abd84cd1">clear</a> ()</td></tr>
<tr class="memdesc:aec9c965448e4dc851d7cacd3abd84cd1 inherit pub_methods_classcv_1_1Algorithm"><td class="mdescLeft"> </td><td class="mdescRight">Clears the algorithm state.  <a href="../../d3/d46/classcv_1_1Algorithm.html#aec9c965448e4dc851d7cacd3abd84cd1">More...</a><br/></td></tr>
<tr class="separator:aec9c965448e4dc851d7cacd3abd84cd1 inherit pub_methods_classcv_1_1Algorithm"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a286fc82744ccab3d248aca44524266a9 inherit pub_methods_classcv_1_1Algorithm"><td align="right" class="memItemLeft" valign="top">virtual <a class="el" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d3/d46/classcv_1_1Algorithm.html#a286fc82744ccab3d248aca44524266a9">getDefaultName</a> () const</td></tr>
<tr class="separator:a286fc82744ccab3d248aca44524266a9 inherit pub_methods_classcv_1_1Algorithm"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:aef2ad3f4145bd6e8c3664eb1c4b5e1e6 inherit pub_methods_classcv_1_1Algorithm"><td align="right" class="memItemLeft" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d3/d46/classcv_1_1Algorithm.html#aef2ad3f4145bd6e8c3664eb1c4b5e1e6">read</a> (const <a class="el" href="../../de/dd9/classcv_1_1FileNode.html">FileNode</a> &amp;fn)</td></tr>
<tr class="memdesc:aef2ad3f4145bd6e8c3664eb1c4b5e1e6 inherit pub_methods_classcv_1_1Algorithm"><td class="mdescLeft"> </td><td class="mdescRight">Reads algorithm parameters from a file storage.  <a href="../../d3/d46/classcv_1_1Algorithm.html#aef2ad3f4145bd6e8c3664eb1c4b5e1e6">More...</a><br/></td></tr>
<tr class="separator:aef2ad3f4145bd6e8c3664eb1c4b5e1e6 inherit pub_methods_classcv_1_1Algorithm"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a0a880744bc4e3f45711444571df47d67 inherit pub_methods_classcv_1_1Algorithm"><td align="right" class="memItemLeft" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d3/d46/classcv_1_1Algorithm.html#a0a880744bc4e3f45711444571df47d67">save</a> (const <a class="el" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a> &amp;filename) const</td></tr>
<tr class="separator:a0a880744bc4e3f45711444571df47d67 inherit pub_methods_classcv_1_1Algorithm"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a1f8ad7b8add515077367fb9949a174d2 inherit pub_methods_classcv_1_1Algorithm"><td align="right" class="memItemLeft" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d3/d46/classcv_1_1Algorithm.html#a1f8ad7b8add515077367fb9949a174d2">write</a> (<a class="el" href="../../da/d56/classcv_1_1FileStorage.html">FileStorage</a> &amp;fs) const</td></tr>
<tr class="memdesc:a1f8ad7b8add515077367fb9949a174d2 inherit pub_methods_classcv_1_1Algorithm"><td class="mdescLeft"> </td><td class="mdescRight">Stores algorithm parameters in a file storage.  <a href="../../d3/d46/classcv_1_1Algorithm.html#a1f8ad7b8add515077367fb9949a174d2">More...</a><br/></td></tr>
<tr class="separator:a1f8ad7b8add515077367fb9949a174d2 inherit pub_methods_classcv_1_1Algorithm"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a763a62d1b03042eef7d7fc3ac6c87c79 inherit pub_methods_classcv_1_1Algorithm"><td align="right" class="memItemLeft" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d3/d46/classcv_1_1Algorithm.html#a763a62d1b03042eef7d7fc3ac6c87c79">write</a> (const <a class="el" href="../../dc/d84/group__core__basic.html#ga6395ca871a678020c4a31fadf7e8cc63">Ptr</a>&lt; <a class="el" href="../../da/d56/classcv_1_1FileStorage.html">FileStorage</a> &gt; &amp;fs, const <a class="el" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a> &amp;name=<a class="el" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a>()) const</td></tr>
<tr class="memdesc:a763a62d1b03042eef7d7fc3ac6c87c79 inherit pub_methods_classcv_1_1Algorithm"><td class="mdescLeft"> </td><td class="mdescRight">simplified API for language bindings This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.  <a href="../../d3/d46/classcv_1_1Algorithm.html#a763a62d1b03042eef7d7fc3ac6c87c79">More...</a><br/></td></tr>
<tr class="separator:a763a62d1b03042eef7d7fc3ac6c87c79 inherit pub_methods_classcv_1_1Algorithm"><td class="memSeparator" colspan="2"> </td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-static-methods"></a>
Static Public Member Functions</h2></td></tr>
<tr class="memitem:aa0ae71ed85f63d2ea809402c0f19d602"><td align="right" class="memItemLeft" valign="top">static <a class="el" href="../../dc/d84/group__core__basic.html#ga6395ca871a678020c4a31fadf7e8cc63">Ptr</a>&lt; <a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html">DTrees</a> &gt; </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#aa0ae71ed85f63d2ea809402c0f19d602">create</a> ()</td></tr>
<tr class="memdesc:aa0ae71ed85f63d2ea809402c0f19d602"><td class="mdescLeft"> </td><td class="mdescRight">Creates the empty model.  <a href="#aa0ae71ed85f63d2ea809402c0f19d602">More...</a><br/></td></tr>
<tr class="separator:aa0ae71ed85f63d2ea809402c0f19d602"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a9a13c065058afce14367ca44739fb4df"><td align="right" class="memItemLeft" valign="top">static <a class="el" href="../../dc/d84/group__core__basic.html#ga6395ca871a678020c4a31fadf7e8cc63">Ptr</a>&lt; <a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html">DTrees</a> &gt; </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#a9a13c065058afce14367ca44739fb4df">load</a> (const <a class="el" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a> &amp;filepath, const <a class="el" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a> &amp;nodeName=<a class="el" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a>())</td></tr>
<tr class="memdesc:a9a13c065058afce14367ca44739fb4df"><td class="mdescLeft"> </td><td class="mdescRight">Loads and creates a serialized <a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html" title="The class represents a single decision tree or a collection of decision trees. ">DTrees</a> from a file.  <a href="#a9a13c065058afce14367ca44739fb4df">More...</a><br/></td></tr>
<tr class="separator:a9a13c065058afce14367ca44739fb4df"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="inherit_header pub_static_methods_classcv_1_1ml_1_1StatModel"><td colspan="2" onclick="javascript:toggleInherit('pub_static_methods_classcv_1_1ml_1_1StatModel')"><img alt="-" src="../../closed.png"/> Static Public Member Functions inherited from <a class="el" href="../../db/d7d/classcv_1_1ml_1_1StatModel.html">cv::ml::StatModel</a></td></tr>
<tr class="memitem:af93a21ea5866cd305936a03742f69af8 inherit pub_static_methods_classcv_1_1ml_1_1StatModel"><td class="memTemplParams" colspan="2">template&lt;typename _Tp &gt; </td></tr>
<tr class="memitem:af93a21ea5866cd305936a03742f69af8 inherit pub_static_methods_classcv_1_1ml_1_1StatModel"><td align="right" class="memTemplItemLeft" valign="top">static <a class="el" href="../../dc/d84/group__core__basic.html#ga6395ca871a678020c4a31fadf7e8cc63">Ptr</a>&lt; _Tp &gt; </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="../../db/d7d/classcv_1_1ml_1_1StatModel.html#af93a21ea5866cd305936a03742f69af8">train</a> (const <a class="el" href="../../dc/d84/group__core__basic.html#ga6395ca871a678020c4a31fadf7e8cc63">Ptr</a>&lt; <a class="el" href="../../dc/d32/classcv_1_1ml_1_1TrainData.html">TrainData</a> &gt; &amp;data, int flags=0)</td></tr>
<tr class="memdesc:af93a21ea5866cd305936a03742f69af8 inherit pub_static_methods_classcv_1_1ml_1_1StatModel"><td class="mdescLeft"> </td><td class="mdescRight">Create and train model with default parameters.  <a href="../../db/d7d/classcv_1_1ml_1_1StatModel.html#af93a21ea5866cd305936a03742f69af8">More...</a><br/></td></tr>
<tr class="separator:af93a21ea5866cd305936a03742f69af8 inherit pub_static_methods_classcv_1_1ml_1_1StatModel"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="inherit_header pub_static_methods_classcv_1_1Algorithm"><td colspan="2" onclick="javascript:toggleInherit('pub_static_methods_classcv_1_1Algorithm')"><img alt="-" src="../../closed.png"/> Static Public Member Functions inherited from <a class="el" href="../../d3/d46/classcv_1_1Algorithm.html">cv::Algorithm</a></td></tr>
<tr class="memitem:a623841c33b58ea9c4847da04607e067b inherit pub_static_methods_classcv_1_1Algorithm"><td class="memTemplParams" colspan="2">template&lt;typename _Tp &gt; </td></tr>
<tr class="memitem:a623841c33b58ea9c4847da04607e067b inherit pub_static_methods_classcv_1_1Algorithm"><td align="right" class="memTemplItemLeft" valign="top">static <a class="el" href="../../dc/d84/group__core__basic.html#ga6395ca871a678020c4a31fadf7e8cc63">Ptr</a>&lt; _Tp &gt; </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="../../d3/d46/classcv_1_1Algorithm.html#a623841c33b58ea9c4847da04607e067b">load</a> (const <a class="el" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a> &amp;filename, const <a class="el" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a> &amp;objname=<a class="el" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a>())</td></tr>
<tr class="memdesc:a623841c33b58ea9c4847da04607e067b inherit pub_static_methods_classcv_1_1Algorithm"><td class="mdescLeft"> </td><td class="mdescRight">Loads algorithm from the file.  <a href="../../d3/d46/classcv_1_1Algorithm.html#a623841c33b58ea9c4847da04607e067b">More...</a><br/></td></tr>
<tr class="separator:a623841c33b58ea9c4847da04607e067b inherit pub_static_methods_classcv_1_1Algorithm"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a3ba305a10d02479c13cf7d169c321547 inherit pub_static_methods_classcv_1_1Algorithm"><td class="memTemplParams" colspan="2">template&lt;typename _Tp &gt; </td></tr>
<tr class="memitem:a3ba305a10d02479c13cf7d169c321547 inherit pub_static_methods_classcv_1_1Algorithm"><td align="right" class="memTemplItemLeft" valign="top">static <a class="el" href="../../dc/d84/group__core__basic.html#ga6395ca871a678020c4a31fadf7e8cc63">Ptr</a>&lt; _Tp &gt; </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="../../d3/d46/classcv_1_1Algorithm.html#a3ba305a10d02479c13cf7d169c321547">loadFromString</a> (const <a class="el" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a> &amp;strModel, const <a class="el" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a> &amp;objname=<a class="el" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a>())</td></tr>
<tr class="memdesc:a3ba305a10d02479c13cf7d169c321547 inherit pub_static_methods_classcv_1_1Algorithm"><td class="mdescLeft"> </td><td class="mdescRight">Loads algorithm from a String.  <a href="../../d3/d46/classcv_1_1Algorithm.html#a3ba305a10d02479c13cf7d169c321547">More...</a><br/></td></tr>
<tr class="separator:a3ba305a10d02479c13cf7d169c321547 inherit pub_static_methods_classcv_1_1Algorithm"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:ad8c591bacb34c485f5b7a250c314fc53 inherit pub_static_methods_classcv_1_1Algorithm"><td class="memTemplParams" colspan="2">template&lt;typename _Tp &gt; </td></tr>
<tr class="memitem:ad8c591bacb34c485f5b7a250c314fc53 inherit pub_static_methods_classcv_1_1Algorithm"><td align="right" class="memTemplItemLeft" valign="top">static <a class="el" href="../../dc/d84/group__core__basic.html#ga6395ca871a678020c4a31fadf7e8cc63">Ptr</a>&lt; _Tp &gt; </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="../../d3/d46/classcv_1_1Algorithm.html#ad8c591bacb34c485f5b7a250c314fc53">read</a> (const <a class="el" href="../../de/dd9/classcv_1_1FileNode.html">FileNode</a> &amp;fn)</td></tr>
<tr class="memdesc:ad8c591bacb34c485f5b7a250c314fc53 inherit pub_static_methods_classcv_1_1Algorithm"><td class="mdescLeft"> </td><td class="mdescRight">Reads algorithm from the file node.  <a href="../../d3/d46/classcv_1_1Algorithm.html#ad8c591bacb34c485f5b7a250c314fc53">More...</a><br/></td></tr>
<tr class="separator:ad8c591bacb34c485f5b7a250c314fc53 inherit pub_static_methods_classcv_1_1Algorithm"><td class="memSeparator" colspan="2"> </td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="inherited"></a>
Additional Inherited Members</h2></td></tr>
<tr class="inherit_header pro_methods_classcv_1_1Algorithm"><td colspan="2" onclick="javascript:toggleInherit('pro_methods_classcv_1_1Algorithm')"><img alt="-" src="../../closed.png"/> Protected Member Functions inherited from <a class="el" href="../../d3/d46/classcv_1_1Algorithm.html">cv::Algorithm</a></td></tr>
<tr class="memitem:a68eeca71617474ad3d4561786f0289d2 inherit pro_methods_classcv_1_1Algorithm"><td align="right" class="memItemLeft" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d3/d46/classcv_1_1Algorithm.html#a68eeca71617474ad3d4561786f0289d2">writeFormat</a> (<a class="el" href="../../da/d56/classcv_1_1FileStorage.html">FileStorage</a> &amp;fs) const</td></tr>
<tr class="separator:a68eeca71617474ad3d4561786f0289d2 inherit pro_methods_classcv_1_1Algorithm"><td class="memSeparator" colspan="2"> </td></tr>
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<a id="details" name="details"></a><h2 class="groupheader">Detailed Description</h2>
<div class="textblock"><p>The class represents a single decision tree or a collection of decision trees. </p>
<p>The current public interface of the class allows user to train only a single decision tree, however the class is capable of storing multiple decision trees and using them for prediction (by summing responses or using a voting schemes), and the derived from <a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html" title="The class represents a single decision tree or a collection of decision trees. ">DTrees</a> classes (such as <a class="el" href="../../d0/d65/classcv_1_1ml_1_1RTrees.html" title="The class implements the random forest predictor. ">RTrees</a> and <a class="el" href="../../d6/d7a/classcv_1_1ml_1_1Boost.html" title="Boosted tree classifier derived from DTrees. ">Boost</a>) use this capability to implement decision tree ensembles.</p>
<dl class="section see"><dt>See also</dt><dd><a class="el" href="../../dc/dd6/ml_intro.html#ml_intro_trees">Decision Trees </a> </dd></dl>
</div><h2 class="groupheader">Member Enumeration Documentation</h2>
<a id="a7afa5cd2289fb88989c0ab1b8b5d8ac2"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a7afa5cd2289fb88989c0ab1b8b5d8ac2">◆ </a></span>Flags</h2>
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          <td class="memname">enum <a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#a7afa5cd2289fb88989c0ab1b8b5d8ac2">cv::ml::DTrees::Flags</a></td>
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<p>Predict options </p>
<table class="fieldtable">
<tr><th colspan="2">Enumerator</th></tr><tr><td class="fieldname"><a id="a7afa5cd2289fb88989c0ab1b8b5d8ac2af0192db97208b67118f642530da47332"></a>PREDICT_AUTO </td><td class="fielddoc"></td></tr>
<tr><td class="fieldname"><a id="a7afa5cd2289fb88989c0ab1b8b5d8ac2a1d3f6687120ea6b337f6a91234529a13"></a>PREDICT_SUM </td><td class="fielddoc"></td></tr>
<tr><td class="fieldname"><a id="a7afa5cd2289fb88989c0ab1b8b5d8ac2ad753bae4672b471203e418d820c00e85"></a>PREDICT_MAX_VOTE </td><td class="fielddoc"></td></tr>
<tr><td class="fieldname"><a id="a7afa5cd2289fb88989c0ab1b8b5d8ac2a59a0cd54206e4092bc2bff1ce50c8afa"></a>PREDICT_MASK </td><td class="fielddoc"></td></tr>
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<h2 class="groupheader">Member Function Documentation</h2>
<a id="aa0ae71ed85f63d2ea809402c0f19d602"></a>
<h2 class="memtitle"><span class="permalink"><a href="#aa0ae71ed85f63d2ea809402c0f19d602">◆ </a></span>create()</h2>
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          <td class="memname">static <a class="el" href="../../dc/d84/group__core__basic.html#ga6395ca871a678020c4a31fadf7e8cc63">Ptr</a>&lt;<a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html">DTrees</a>&gt; cv::ml::DTrees::create </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
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<span class="mlabels"><span class="mlabel">static</span></span>  </td>
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<p>Creates the empty model. </p>
<p>The static method creates empty decision tree with the specified parameters. It should be then trained using train method (see <a class="el" href="../../db/d7d/classcv_1_1ml_1_1StatModel.html#af96a0e04f1677a835cc25263c7db3c0c" title="Trains the statistical model. ">StatModel::train</a>). Alternatively, you can load the model from file using <a class="el" href="../../d3/d46/classcv_1_1Algorithm.html#a623841c33b58ea9c4847da04607e067b" title="Loads algorithm from the file. ">Algorithm::load</a>&lt;<a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html" title="The class represents a single decision tree or a collection of decision trees. ">DTrees</a>&gt;(filename). </p>
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<a id="abfced3f2d3bf13b39c94e4a3fecc4309"></a>
<h2 class="memtitle"><span class="permalink"><a href="#abfced3f2d3bf13b39c94e4a3fecc4309">◆ </a></span>getCVFolds()</h2>
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          <td class="memname">virtual int cv::ml::DTrees::getCVFolds </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td> const</td>
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<span class="mlabels"><span class="mlabel">pure virtual</span></span>  </td>
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</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.ml_DTrees.getCVFolds(</td><td class="paramname"></td><td>)</td></tr></table>
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<p>If CVFolds &gt; 1 then algorithms prunes the built decision tree using K-fold cross-validation procedure where K is equal to CVFolds. Default value is 10. </p><dl class="section see"><dt>See also</dt><dd><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#a082ed33b1dd2101152dd33bdc2847404">setCVFolds</a> </dd></dl>
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<a id="ad7dea805ae861c26fdd0b79eb34b3c24"></a>
<h2 class="memtitle"><span class="permalink"><a href="#ad7dea805ae861c26fdd0b79eb34b3c24">◆ </a></span>getMaxCategories()</h2>
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          <td class="memname">virtual int cv::ml::DTrees::getMaxCategories </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td> const</td>
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<span class="mlabels"><span class="mlabel">pure virtual</span></span>  </td>
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</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.ml_DTrees.getMaxCategories(</td><td class="paramname"></td><td>)</td></tr></table>
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<p>Cluster possible values of a categorical variable into K&lt;=maxCategories clusters to find a suboptimal split. If a discrete variable, on which the training procedure tries to make a split, takes more than maxCategories values, the precise best subset estimation may take a very long time because the algorithm is exponential. Instead, many decision trees engines (including our implementation) try to find sub-optimal split in this case by clustering all the samples into maxCategories clusters that is some categories are merged together. The clustering is applied only in n &gt; 2-class classification problems for categorical variables with N &gt; max_categories possible values. In case of regression and 2-class classification the optimal split can be found efficiently without employing clustering, thus the parameter is not used in these cases. Default value is 10. </p><dl class="section see"><dt>See also</dt><dd><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#a6d1571c10e5d72f8df7f102b916d704f">setMaxCategories</a> </dd></dl>
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<a id="ac41b80cb9e2ea0d477425052f9692104"></a>
<h2 class="memtitle"><span class="permalink"><a href="#ac41b80cb9e2ea0d477425052f9692104">◆ </a></span>getMaxDepth()</h2>
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          <td class="memname">virtual int cv::ml::DTrees::getMaxDepth </td>
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          <td class="paramname"></td><td>)</td>
          <td> const</td>
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<span class="mlabels"><span class="mlabel">pure virtual</span></span>  </td>
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</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.ml_DTrees.getMaxDepth(</td><td class="paramname"></td><td>)</td></tr></table>
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<p>The maximum possible depth of the tree. That is the training algorithms attempts to split a node while its depth is less than maxDepth. The root node has zero depth. The actual depth may be smaller if the other termination criteria are met (see the outline of the training procedure <a class="el" href="../../dc/dd6/ml_intro.html#ml_intro_trees">here</a>), and/or if the tree is pruned. Default value is INT_MAX. </p><dl class="section see"><dt>See also</dt><dd><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#ab2192b5631da2d30eaaebdb12015f477">setMaxDepth</a> </dd></dl>
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<h2 class="memtitle"><span class="permalink"><a href="#a277c2ccecfa7fc65d1d474b56450e126">◆ </a></span>getMinSampleCount()</h2>
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          <td class="memname">virtual int cv::ml::DTrees::getMinSampleCount </td>
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          <td class="paramname"></td><td>)</td>
          <td> const</td>
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<span class="mlabels"><span class="mlabel">pure virtual</span></span>  </td>
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<p>If the number of samples in a node is less than this parameter then the node will not be split.</p>
<p>Default value is 10. </p><dl class="section see"><dt>See also</dt><dd><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#abe34fc6e9a172b9e334abcca94e28fb6">setMinSampleCount</a> </dd></dl>
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<h2 class="memtitle"><span class="permalink"><a href="#ae4ffa17349a0094c5cded6e92042ffc2">◆ </a></span>getNodes()</h2>
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          <td class="memname">virtual const std::vector&lt;<a class="el" href="../../d4/d7d/classcv_1_1ml_1_1DTrees_1_1Node.html">Node</a>&gt;&amp; cv::ml::DTrees::getNodes </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td> const</td>
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<p>Returns all the nodes. </p>
<p>all the node indices are indices in the returned vector </p>
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<h2 class="memtitle"><span class="permalink"><a href="#a152badc1f5a4963ef9d43d7e7395bd3b">◆ </a></span>getPriors()</h2>
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          <td class="memname">virtual <a class="el" href="../../d3/d63/classcv_1_1Mat.html">cv::Mat</a> cv::ml::DTrees::getPriors </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td> const</td>
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<span class="mlabels"><span class="mlabel">pure virtual</span></span>  </td>
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<p>The array of a priori class probabilities, sorted by the class label value. </p>
<p>The parameter can be used to tune the decision tree preferences toward a certain class. For example, if you want to detect some rare anomaly occurrence, the training base will likely contain much more normal cases than anomalies, so a very good classification performance will be achieved just by considering every case as normal. To avoid this, the priors can be specified, where the anomaly probability is artificially increased (up to 0.5 or even greater), so the weight of the misclassified anomalies becomes much bigger, and the tree is adjusted properly.</p>
<p>You can also think about this parameter as weights of prediction categories which determine relative weights that you give to misclassification. That is, if the weight of the first category is 1 and the weight of the second category is 10, then each mistake in predicting the second category is equivalent to making 10 mistakes in predicting the first category. Default value is empty <a class="el" href="../../d3/d63/classcv_1_1Mat.html" title="n-dimensional dense array class ">Mat</a>. </p><dl class="section see"><dt>See also</dt><dd><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#a66756433f31db77a5511fc3f85403bd9" title="The array of a priori class probabilities, sorted by the class label value. ">setPriors</a> </dd></dl>
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<a id="ab7ec8342deddac53ebbb92145c992db7"></a>
<h2 class="memtitle"><span class="permalink"><a href="#ab7ec8342deddac53ebbb92145c992db7">◆ </a></span>getRegressionAccuracy()</h2>
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          <td class="memname">virtual float cv::ml::DTrees::getRegressionAccuracy </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td> const</td>
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<span class="mlabels"><span class="mlabel">pure virtual</span></span>  </td>
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</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.ml_DTrees.getRegressionAccuracy(</td><td class="paramname"></td><td>)</td></tr></table>
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<p>Termination criteria for regression trees. If all absolute differences between an estimated value in a node and values of train samples in this node are less than this parameter then the node will not be split further. Default value is 0.01f </p><dl class="section see"><dt>See also</dt><dd><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#a936a3b56ccc5684f279dfd76bbea0247">setRegressionAccuracy</a> </dd></dl>
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<h2 class="memtitle"><span class="permalink"><a href="#af99b15e5769c614bb1f1e16330b6fa4f">◆ </a></span>getRoots()</h2>
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          <td class="memname">virtual const std::vector&lt;int&gt;&amp; cv::ml::DTrees::getRoots </td>
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          <td class="paramname"></td><td>)</td>
          <td> const</td>
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<p>Returns indices of root nodes. </p>
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<h2 class="memtitle"><span class="permalink"><a href="#a23bd587736aa6c658966025cfff3f4a3">◆ </a></span>getSplits()</h2>
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          <td class="memname">virtual const std::vector&lt;<a class="el" href="../../d9/d37/classcv_1_1ml_1_1DTrees_1_1Split.html">Split</a>&gt;&amp; cv::ml::DTrees::getSplits </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td> const</td>
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<p>Returns all the splits. </p>
<p>all the split indices are indices in the returned vector </p>
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<h2 class="memtitle"><span class="permalink"><a href="#ab4edebdd513c1937dfa8f444931f6a7a">◆ </a></span>getSubsets()</h2>
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          <td class="paramname"></td><td>)</td>
          <td> const</td>
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<p>Returns all the bitsets for categorical splits. </p>
<p><a class="el" href="../../d9/d37/classcv_1_1ml_1_1DTrees_1_1Split.html#afd2ee09de243483ccbbd9bd5a0676f2f">Split::subsetOfs</a> is an offset in the returned vector </p>
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<h2 class="memtitle"><span class="permalink"><a href="#a905b23962a6c393a87b79bcc086cc6c2">◆ </a></span>getTruncatePrunedTree()</h2>
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          <td class="memname">virtual bool cv::ml::DTrees::getTruncatePrunedTree </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td> const</td>
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<span class="mlabels"><span class="mlabel">pure virtual</span></span>  </td>
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<p>If true then pruned branches are physically removed from the tree. Otherwise they are retained and it is possible to get results from the original unpruned (or pruned less aggressively) tree. Default value is true. </p><dl class="section see"><dt>See also</dt><dd><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#a6f2663a08abc3e872bd3f3a53a84615c">setTruncatePrunedTree</a> </dd></dl>
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<h2 class="memtitle"><span class="permalink"><a href="#a5d8bd6934507c56905f93b5b8c7d1584">◆ </a></span>getUse1SERule()</h2>
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          <td class="memname">virtual bool cv::ml::DTrees::getUse1SERule </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td> const</td>
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<span class="mlabels"><span class="mlabel">pure virtual</span></span>  </td>
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</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.ml_DTrees.getUse1SERule(</td><td class="paramname"></td><td>)</td></tr></table>
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<p>If true then a pruning will be harsher. This will make a tree more compact and more resistant to the training data noise but a bit less accurate. Default value is true. </p><dl class="section see"><dt>See also</dt><dd><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#a08089831f9a07e0ce6a5e5faccdf31f6">setUse1SERule</a> </dd></dl>
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<h2 class="memtitle"><span class="permalink"><a href="#a566708bb8841067f146afae81b6219f4">◆ </a></span>getUseSurrogates()</h2>
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          <td class="memname">virtual bool cv::ml::DTrees::getUseSurrogates </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td> const</td>
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  </td>
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<span class="mlabels"><span class="mlabel">pure virtual</span></span>  </td>
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</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.ml_DTrees.getUseSurrogates(</td><td class="paramname"></td><td>)</td></tr></table>
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<p>If true then surrogate splits will be built. These splits allow to work with missing data and compute variable importance correctly. Default value is false. </p><dl class="section note"><dt>Note</dt><dd>currently it's not implemented. </dd></dl>
<dl class="section see"><dt>See also</dt><dd><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#a33d8fec217d423609a9f29a0a787111c">setUseSurrogates</a> </dd></dl>
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<h2 class="memtitle"><span class="permalink"><a href="#a9a13c065058afce14367ca44739fb4df">◆ </a></span>load()</h2>
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          <td class="memname">static <a class="el" href="../../dc/d84/group__core__basic.html#ga6395ca871a678020c4a31fadf7e8cc63">Ptr</a>&lt;<a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html">DTrees</a>&gt; cv::ml::DTrees::load </td>
          <td>(</td>
          <td class="paramtype">const <a class="el" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a> &amp; </td>
          <td class="paramname"><em>filepath</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const <a class="el" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a> &amp; </td>
          <td class="paramname"><em>nodeName</em> = <code><a class="el" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a>()</code> </td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
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<span class="mlabels"><span class="mlabel">static</span></span>  </td>
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</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.ml.DTrees_load(</td><td class="paramname">filepath[, nodeName]</td><td>)</td></tr></table>
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<p>Loads and creates a serialized <a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html" title="The class represents a single decision tree or a collection of decision trees. ">DTrees</a> from a file. </p>
<p>Use DTree::save to serialize and store an DTree to disk. Load the DTree from this file again, by calling this function with the path to the file. Optionally specify the node for the file containing the classifier</p>
<dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramname">filepath</td><td>path to serialized DTree </td></tr>
    <tr><td class="paramname">nodeName</td><td>name of node containing the classifier </td></tr>
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  </dd>
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<h2 class="memtitle"><span class="permalink"><a href="#a082ed33b1dd2101152dd33bdc2847404">◆ </a></span>setCVFolds()</h2>
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          <td class="memname">virtual void cv::ml::DTrees::setCVFolds </td>
          <td>(</td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>val</em></td><td>)</td>
          <td></td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">pure virtual</span></span>  </td>
  </tr>
</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>None</td><td>=</td><td>cv.ml_DTrees.setCVFolds(</td><td class="paramname">val</td><td>)</td></tr></table>
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<p></p>
<dl class="section see"><dt>See also</dt><dd><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#abfced3f2d3bf13b39c94e4a3fecc4309">getCVFolds</a> </dd></dl>
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<h2 class="memtitle"><span class="permalink"><a href="#a6d1571c10e5d72f8df7f102b916d704f">◆ </a></span>setMaxCategories()</h2>
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          <td class="memname">virtual void cv::ml::DTrees::setMaxCategories </td>
          <td>(</td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>val</em></td><td>)</td>
          <td></td>
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      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">pure virtual</span></span>  </td>
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</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>None</td><td>=</td><td>cv.ml_DTrees.setMaxCategories(</td><td class="paramname">val</td><td>)</td></tr></table>
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<p></p>
<dl class="section see"><dt>See also</dt><dd><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#ad7dea805ae861c26fdd0b79eb34b3c24">getMaxCategories</a> </dd></dl>
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<h2 class="memtitle"><span class="permalink"><a href="#ab2192b5631da2d30eaaebdb12015f477">◆ </a></span>setMaxDepth()</h2>
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          <td class="memname">virtual void cv::ml::DTrees::setMaxDepth </td>
          <td>(</td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>val</em></td><td>)</td>
          <td></td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">pure virtual</span></span>  </td>
  </tr>
</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>None</td><td>=</td><td>cv.ml_DTrees.setMaxDepth(</td><td class="paramname">val</td><td>)</td></tr></table>
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<p></p>
<dl class="section see"><dt>See also</dt><dd><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#ac41b80cb9e2ea0d477425052f9692104">getMaxDepth</a> </dd></dl>
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<h2 class="memtitle"><span class="permalink"><a href="#abe34fc6e9a172b9e334abcca94e28fb6">◆ </a></span>setMinSampleCount()</h2>
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          <td class="memname">virtual void cv::ml::DTrees::setMinSampleCount </td>
          <td>(</td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>val</em></td><td>)</td>
          <td></td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">pure virtual</span></span>  </td>
  </tr>
</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>None</td><td>=</td><td>cv.ml_DTrees.setMinSampleCount(</td><td class="paramname">val</td><td>)</td></tr></table>
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<p></p>
<dl class="section see"><dt>See also</dt><dd><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#a277c2ccecfa7fc65d1d474b56450e126">getMinSampleCount</a> </dd></dl>
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<h2 class="memtitle"><span class="permalink"><a href="#a66756433f31db77a5511fc3f85403bd9">◆ </a></span>setPriors()</h2>
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          <td class="memname">virtual void cv::ml::DTrees::setPriors </td>
          <td>(</td>
          <td class="paramtype">const <a class="el" href="../../d3/d63/classcv_1_1Mat.html">cv::Mat</a> &amp; </td>
          <td class="paramname"><em>val</em></td><td>)</td>
          <td></td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">pure virtual</span></span>  </td>
  </tr>
</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>None</td><td>=</td><td>cv.ml_DTrees.setPriors(</td><td class="paramname">val</td><td>)</td></tr></table>
</div><div class="memdoc">
<p>The array of a priori class probabilities, sorted by the class label value. </p>
<dl class="section see"><dt>See also</dt><dd><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#a152badc1f5a4963ef9d43d7e7395bd3b" title="The array of a priori class probabilities, sorted by the class label value. ">getPriors</a> </dd></dl>
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<h2 class="memtitle"><span class="permalink"><a href="#a936a3b56ccc5684f279dfd76bbea0247">◆ </a></span>setRegressionAccuracy()</h2>
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          <td class="memname">virtual void cv::ml::DTrees::setRegressionAccuracy </td>
          <td>(</td>
          <td class="paramtype">float </td>
          <td class="paramname"><em>val</em></td><td>)</td>
          <td></td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">pure virtual</span></span>  </td>
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</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>None</td><td>=</td><td>cv.ml_DTrees.setRegressionAccuracy(</td><td class="paramname">val</td><td>)</td></tr></table>
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<p></p>
<dl class="section see"><dt>See also</dt><dd><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#ab7ec8342deddac53ebbb92145c992db7">getRegressionAccuracy</a> </dd></dl>
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<h2 class="memtitle"><span class="permalink"><a href="#a6f2663a08abc3e872bd3f3a53a84615c">◆ </a></span>setTruncatePrunedTree()</h2>
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          <td class="memname">virtual void cv::ml::DTrees::setTruncatePrunedTree </td>
          <td>(</td>
          <td class="paramtype">bool </td>
          <td class="paramname"><em>val</em></td><td>)</td>
          <td></td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">pure virtual</span></span>  </td>
  </tr>
</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>None</td><td>=</td><td>cv.ml_DTrees.setTruncatePrunedTree(</td><td class="paramname">val</td><td>)</td></tr></table>
</div><div class="memdoc">
<p></p>
<dl class="section see"><dt>See also</dt><dd><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#a905b23962a6c393a87b79bcc086cc6c2">getTruncatePrunedTree</a> </dd></dl>
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<h2 class="memtitle"><span class="permalink"><a href="#a08089831f9a07e0ce6a5e5faccdf31f6">◆ </a></span>setUse1SERule()</h2>
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  <td class="mlabels-left">
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          <td class="memname">virtual void cv::ml::DTrees::setUse1SERule </td>
          <td>(</td>
          <td class="paramtype">bool </td>
          <td class="paramname"><em>val</em></td><td>)</td>
          <td></td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">pure virtual</span></span>  </td>
  </tr>
</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>None</td><td>=</td><td>cv.ml_DTrees.setUse1SERule(</td><td class="paramname">val</td><td>)</td></tr></table>
</div><div class="memdoc">
<p></p>
<dl class="section see"><dt>See also</dt><dd><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#a5d8bd6934507c56905f93b5b8c7d1584">getUse1SERule</a> </dd></dl>
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<a id="a33d8fec217d423609a9f29a0a787111c"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a33d8fec217d423609a9f29a0a787111c">◆ </a></span>setUseSurrogates()</h2>
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          <td class="memname">virtual void cv::ml::DTrees::setUseSurrogates </td>
          <td>(</td>
          <td class="paramtype">bool </td>
          <td class="paramname"><em>val</em></td><td>)</td>
          <td></td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">pure virtual</span></span>  </td>
  </tr>
</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>None</td><td>=</td><td>cv.ml_DTrees.setUseSurrogates(</td><td class="paramname">val</td><td>)</td></tr></table>
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<dl class="section see"><dt>See also</dt><dd><a class="el" href="../../d8/d89/classcv_1_1ml_1_1DTrees.html#a566708bb8841067f146afae81b6219f4">getUseSurrogates</a> </dd></dl>
</div>
</div>
<hr/>The documentation for this class was generated from the following file:<ul>
<li>opencv2/<a class="el" href="../../d3/d29/ml_8hpp.html">ml.hpp</a></li>
</ul>
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